Prediction of color changes in acetaminophen solution using the time–temperature superposition principle

A prediction method for color changes based on the time–temperature superposition principle (TTSP) was developed for acetaminophen solution. Color changes of acetaminophen solution are caused by the degradation of acetaminophen, such as hydrolysis and oxidation. In principle, the TTSP can be applied to only thermal aging. Therefore, the impact of oxidation on the color changes of acetaminophen solution was verified. The results of our experiment suggested that the oxidation products enhanced the color changes in acetaminophen solution. Next, the color changes of acetaminophen solution samples of the same head space volume after accelerated aging at various temperatures were investigated using the Commission Internationale de l’Eclairage (CIE) LAB color space (a*, b*, L* and ΔE*ab), following which the TTSP was adopted to kinetic analysis of the color changes. The apparent activation energies using the time–temperature shift factor of a*, b*, L* and ΔE*ab were calculated as 72.4, 69.2, 72.3 and 70.9 (kJ/mol), respectively, which are similar to the values for acetaminophen hydrolysis reported in the literature. The predicted values of a*, b*, L* and ΔE*ab at 40?°C were obtained by calculation using Arrhenius plots. A comparison between the experimental and predicted values for each color parameter revealed sufficiently high R² values (>0.98), suggesting the high reliability of the prediction. The kinetic analysis using TTSP was successfully applied to predicting the color changes under the controlled oxygen amount at any temperature and for any length of time.     

Fabrication of large-volume microfluidic chamber embedded in glass using three-dimensional femtosecond laser micromachining

We report on fabrication of large-volume, square-shaped microfluidic chamber embedded in glass by scanning a tightly focused femtosecond laser beam inside a porous glass immersed in water. After the hollow structure is created in the porous glass substrate, the fabricated glass sample is post-annealed at 1,050°C during which it can be sintered into a compact glass. By the use of this technique, a 1 mm × 1 mm × 100 μm microchamber connected to four microfluidic channels is created inside the transparent glass substrate, showing that our technique allows for fabrication of not only thin channel structures with arbitrary lengths and configurations, but also hollow structures with infinitely large sizes.     

A reduction method of dynamic false contour utilizing the frame‐rate‐control method with suppression of the side effect on PDPs

Abstract— The plasma‐display panel (PDP) is a type of flat‐panel display that can display a high‐quality image. However, when moving images are displayed, annoying disturbances such as false contour noise occurs. This noise is called dynamic false contour (DFC). To achieve a higher‐quality image, DFC has to be reduced. Therefore, a new method to reduce DFC is proposed. To find a way to reduce DFC, a new evaluation value for it has been defined: the evaluation value of dynamic false contour (EVDFC). This value is defined on the basis of a person's subjective evaluation. By applying this value, the cause that generates DFC can be identified. On the basis of these studies, a new method for reducing DFC by applying frame‐rate control (FRC) with suppression of the side effect is proposed. This improved method can be used to provide high‐quality images.     

Level-of-Detail Rendering of Large-Scale Irregular Volume Datasets Using Particles

This paper describes a level-of-detail rendering technique for large-scale irregular volume datasets. It is well known that the memory bandwidth consumed by visibility sorting becomes the limiting factor when carrying out volume rendering of such datasets. To develop a sorting-free volume rendering technique, we previously proposed a particle-based technique that generates opaque and emissive particles using a density function constant within an irregular volume cell and projects the particles onto an image plane with sub-pixels. When the density function changes significantly in an irregular volume cell, the cell boundary may become prominent, which can cause blocky noise. When the number of the sub-pixels increases, the required frame buffer tends to be large. To solve this problem, this work proposes a new particle-based volume rendering which generates particles using metropolis sampling and renders the particles using the ensemble average. To confirm the effectiveness of this method, we applied our proposed technique to several irregular volume datasets, with the result that the ensemble average outperforms the sub-pixel average in computational complexity and memory usage. In addition, the ensemble average technique allowed us to implement a level of detail in the interactive rendering of a 71-million-cell hexahedral volume dataset and a 26-million-cell quadratic tetrahedral volume dataset.     

Incremental learning of gestures for human–robot interaction

For a robot to cohabit with people, it should be able to learn people’s nonverbal social behavior from experience. In this paper, we propose a novel machine learning method for recognizing gestures used in interaction and communication. Our method enables robots to learn gestures incrementally during human–robot interaction in an unsupervised manner. It allows the user to leave the number and types of gestures undefined prior to the learning. The proposed method (HB-SOINN) is based on a self-organizing incremental neural network and the hidden Markov model. We have added an interactive learning mechanism to HB-SOINN to prevent a single cluster from running into a failure as a result of polysemy of being assigned more than one meaning. For example, a sentence: “Keep on going left slowly” has three meanings such as, “Keep on (1)”, “going left (2)”, “slowly (3)”. We experimentally tested the clustering performance of the proposed method against data obtained from measuring gestures using a motion capture device. The results show that the classification performance of HB-SOINN exceeds that of conventional clustering approaches. In addition, we have found that the interactive learning function improves the learning performance of HB-SOINN.     

Multi agent architecture for dynamic incremental process planning in the flexible manufacturing system

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer’s needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.     

Particle-based multiple irregular volume rendering on CUDA

In this paper, we describe an improved particle-based volume rendering (PBVR) technique for previewing a large irregular volume dataset using the CUDA architecture. This technique allows for opaque and emissive particles to render translucent volumes without visibility sorting. Our GPU acceleration of PBVR provides the multi-volume rendering feature while remaining compatible with both regular and irregular volumes. We also reduce the memory cost required for storing all sub-pixel values by proposing a pixel repetition technique for a large sub-pixel level. By adjusting the repetition level, we achieved a very smooth level of detail (LOD) control for trading quality for speed. Our work demonstrates a full-detail rendering rate from 5 to 10 fps for irregular volume data with mega-scale cell numbers on an NVIDIA GeForce 8800GTS.     

Deformation characteristics of ultra-thin liquid film considering temperature and film thickness dependence of surface tension

Thermocapillary deformations of an ultra-thin liquid film caused by temperature distribution were three-dimensionally analyzed using the unsteady and linearized long wave equation considering the temperature and film thickness dependence of surface tension. The temperature and film thickness dependence equation for the surface tension of a liquid was firstly established. The temperature dependence of the surface tension was obtained experimentally using a surface tensiometer and the film thickness dependence was obtained theoretically from the corrected van der Waals pressure equation for a symmetric multilayer system. Time evolutions of depression and groove of the ultra-thin liquid film caused by local heating were obtained quantitatively.     

Solving the irregular strip packing problem via guided local search for overlap minimization

The irregular strip-packing problem (ISP) requires a given set of non-convex polygons to be placed without overlap within a rectangular container having a fixed width and a variable length, which is to be minimized. As a core sub-problem to solve ISP, we consider an overlap minimization problem (OMP) whose objective is to place all polygons into a container with given width and length so that the total amount of overlap between polygons is made as small as possible. We propose to use directional penetration depths to measure the amount of overlap between a pair of polygons, and present an efficient algorithm to find a position with the minimum overlap for each polygon when it is translated in a specified direction. Based on this, we develop a local search algorithm for OMP that translates a polygon in horizontal and vertical directions alternately. Then we incorporate it in our algorithm for OMP, which is a variant of the guided local search algorithm. Computational results show that our algorithm improves the best-known values of some well-known benchmark instances.